ArticleeLife2022
The unmitigated profile of COVID-19 infectiousness.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- The Wells-Riley Model Revisited II: Parameter Uncertainty and Population Heterogeneity.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- Best practices for estimating and reporting epidemiological delay distributions of infectious diseases.PLoS computational biology · 2024Article
- Incorporating testing volume into estimation of effective reproduction number dynamics.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2024Article
- Detecting changes in generation and serial intervals under varying pathogen biology, contact patterns and outbreak response.PLoS computational biology · 2024Article
- Disentangling the role of virus infectiousness and awareness-based human behavior during the early phase of the COVID-19 pandemic in the European Union.Applied mathematical modelling · 2023Article
- Inferring the differences in incubation-period and generation-interval distributions of the Delta and Omicron variants of SARS-CoV-2.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- A statistical framework for tracking the time-varying superspreading potential of COVID-19 epidemic.Epidemics · 2023Article
- Inferring time-varying generation time, serial interval, and incubation period distributions for COVID-19.Nature communications · 2022Article
- Correlation between times to SARS-CoV-2 symptom onset and secondary transmission undermines epidemic control efforts.Epidemics · 2022Article
- The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants.Journal of the Royal Society, Interface · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Quantifying the temporal dynamics of infectiousness of individuals infected with SARS-CoV-2 is crucial for understanding the spread of COVID-19 and for evaluating the effectiveness of mitigation strategies. Many studies have estimated the infectiousness profile using observed serial intervals. However, statistical and epidemiological biases could lead to underestimation of the duration of infectiousness. We correct for these biases by curating data from the initial outbreak of the pandemic in China (when mitigation was minimal), and find that the infectiousness profile of the original strain is longer than previously thought. Sensitivity analysis shows our results are robust to model structure, assumed growth rate and potential observational biases. Although unmitigated transmission data is lacking for variants of concern (VOCs), previous analyses suggest that the alpha and delta variants have faster within-host kinetics, which we extrapolate to crude estimates of variant-specific unmitigated generation intervals. Knowing the unmitigated infectiousness profile of infected individuals can inform estimates of the effectiveness of isolation and quarantine measures. The framework presented here can help design better quarantine policies in early stages of future epidemics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.